class_docstr: Block for the initial feature downsampling.
  
  Attributes:
    input_shape: Tuple with the input shape i.e. (None, 512, 512, 3).
    out_dims: Integer tuple, number of filter in the first and second
      convolutions.
    norm_type: Object type of the norm to use.
code: def call(self, inputs, **kwargs):
      x = self.conv_block(inputs)
      x = self.residual_block(x)
      return x
  
imports: import gin
  import tensorflow
  from tensorflow_graphics.projects.points_to_3Dobjects.networks import networks
  import tensorflow_graphics.projects.points_to_3Dobjects.networks.custom_blocks
label_desc: Use image node_id 2 for calling the InputDownsampleBlock obj's underlying member method code with example usage: obj.call(inputs) and returns: x